{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import math\n",
    "import json\n",
    "import time\n",
    "import itertools\n",
    "import pickle\n",
    "from scipy import stats\n",
    "import psycopg2 as psql\n",
    "from psycopg2.extras import RealDictCursor\n",
    "\n",
    "import sys\n",
    "sys.path.append(\"..\")\n",
    "from tools.flight_projection import *\n",
    "from tools.conflict_handling import *\n",
    "\n",
    "import seaborn as sns\n",
    "sns.set(color_codes=True)\n",
    "\n",
    "try:\n",
    "    conn = psql.connect(\"dbname='thesisdata' user='postgres' host='localhost' password='postgres'\")\n",
    "except Exception as e:\n",
    "    print(\"Unable to connect to the database.\")\n",
    "    print(e)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Progress: 1 / 2\n",
      "Progress: 2 / 2\n"
     ]
    }
   ],
   "source": [
    "cur_read = conn.cursor(cursor_factory=RealDictCursor)\n",
    "cur_read.execute(\"SELECT * FROM public.converging_ctfm_flights limit 5;\")\n",
    "batch = cur_read.fetchall()\n",
    "\n",
    "cur_read = conn.cursor(cursor_factory=RealDictCursor)\n",
    "cur_read.execute(\"SELECT * FROM public.ctfm_conflicts limit 5;\")\n",
    "batch_2 = cur_read.fetchall()\n",
    "\n",
    "batch.extend(batch_2)\n",
    "conn.close()\n",
    "\n",
    "n_cores = 7\n",
    "b_list = [batch[i:i + n_cores] for i in range(0, len(batch), n_cores)]\n",
    "\n",
    "processed_batch = []\n",
    "\n",
    "for i, r in enumerate(b_list):\n",
    "    res = preprocess_intent_conflicts(r)\n",
    "    processed_batch.append(res)\n",
    "    print(\"Progress: %d / %d\" % (i+1, len(b_list)))\n",
    "\n",
    "# Evaluating Conflicts\n",
    "\n",
    "res = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "intent_flag = True\n",
    "\n",
    "for i, bx in enumerate(processed_batch):\n",
    "    exp_keys = ['ts_1', 'ts_2', 'lat_1', 'lon_1', 'lat_2', 'lon_2', 'hdg_1',\n",
    "                'hdg_2', 'hdg_e_1', 'hdg_e_2', 'spd_1', 'spd_2', 'spd_e_1',\n",
    "                'spd_e_2']\n",
    "\n",
    "    if intent_flag:\n",
    "        exp_keys.extend(['wp_seg_1', 'wp_seg_2'])\n",
    "\n",
    "    ttc_res = []\n",
    "\n",
    "    _pct_dict = {}\n",
    "    pcti = None\n",
    "\n",
    "    confl_count = 0\n",
    "    non_confl_count = 0\n",
    "\n",
    "    for bi in bx:\n",
    "\n",
    "        ttc_res_i = []\n",
    "        b = {}\n",
    "\n",
    "        for k in exp_keys:\n",
    "            try:\n",
    "                b[k] = bi[k]\n",
    "            except Exception as e:\n",
    "                print(e)\n",
    "                print('Not all keys present in flight dictionary')\n",
    "                continue\n",
    "\n",
    "        confl_flag = []\n",
    "\n",
    "        for i in range(len(b['ts_1'])):\n",
    "            confl_flag.append(confl_check(b['lat_1'][i], b['lon_1'][i],\n",
    "                                          b['lat_2'][i], b['lon_2'][i]))\n",
    "\n",
    "        confl_ix = np.where(np.array(confl_flag) > 0)[0]\n",
    "\n",
    "        if len(confl_ix) > 0:\n",
    "            confl_i = confl_ix[0]\n",
    "            confl_ts = b['ts_1'][confl_i]\n",
    "\n",
    "        else:\n",
    "            confl_ts = None\n",
    "\n",
    "        if confl_ts:\n",
    "            print('conflict')\n",
    "            tmax = confl_ts\n",
    "            confl_count = confl_count + 1\n",
    "        else:\n",
    "            tmax = b['ts_1'][-1]\n",
    "            non_confl_count = non_confl_count + 1\n",
    "            \n",
    "\n",
    "            for i, t in enumerate(b['ts_1']):\n",
    "\n",
    "                wp_list_1 = [(wp[2][2], wp[2][3]) for wp in b['wp_seg_1'][i:]]\n",
    "                wp_list_2 = [(wp[2][2], wp[2][3]) for wp in b['wp_seg_2'][i:]]\n",
    "\n",
    "                if not wp_list_1:\n",
    "                    wp_list_1 = [(b['wp_seg_1'][-1][2][2],\n",
    "                                  b['wp_seg_1'][-1][2][3])]\n",
    "                if not wp_list_2:\n",
    "                    wp_list_2 = [(b['wp_seg_2'][-1][2][2],\n",
    "                                  b['wp_seg_2'][-1][2][3])]\n",
    "\n",
    "                if t > tmax:\n",
    "                    break\n",
    "\n",
    "                if confl_ts:\n",
    "                    ttc_act_i = confl_ts - b['ts_1'][i]\n",
    "                    t_la_max = int((tmax - b['ts_1'][i]) * 2)\n",
    "                else:\n",
    "                    ttc_act_i = np.nan\n",
    "                    t_la_max = int(tmax - b['ts_1'][i])\n",
    "                    \n",
    "                lat_1, lon_1, lat_2, lon_2, hdg_1, \\\n",
    "                       hdg_2, spd_1, spd_2, _tmax, _wps_1, _wps_2 = b['lat_1'][i], b['lon_1'][i],b['lat_2'][i], \\\n",
    "                                                    b['lon_2'][i],b['hdg_e_1'][i],b['hdg_e_2'][i], \\\n",
    "                                                    b['spd_e_1'][i],b['spd_e_2'][i], t_la_max, wp_list_1, wp_list_2\n",
    "\n",
    "                wps_seq_1 = sequentialize(_wps_1)\n",
    "                wps_seq_2 = sequentialize(_wps_2)\n",
    "\n",
    "                lat_n_1, lon_n_1, lat_n_2, lon_n_2 = lat_1, lon_1, lat_2, lon_2\n",
    "\n",
    "                if not len(wps_seq_1) < 2:\n",
    "                    wp1_curr_iter = iter(wps_seq_1)\n",
    "                    wp1_next_iter = iter(wps_seq_1[1:])\n",
    "                    _wp1_curr = next(wp1_curr_iter, wps_seq_1[-2])\n",
    "                    _wp1_next = next(wp1_next_iter, wps_seq_1[-1])\n",
    "\n",
    "                else:\n",
    "                    wp1_curr_iter, wp1_next_iter, _wp1_curr, _wp1_next = \\\n",
    "                        None, None, None, None\n",
    "\n",
    "                if not len(wps_seq_2) < 2:\n",
    "                    wp2_curr_iter = iter(wps_seq_2)\n",
    "                    wp2_next_iter = iter(wps_seq_2[1:])\n",
    "                    _wp2_curr = next(wp2_curr_iter, wps_seq_2[-2])\n",
    "                    _wp2_next = next(wp2_next_iter, wps_seq_2[-1])\n",
    "\n",
    "                else:\n",
    "                    wp2_curr_iter, wp2_next_iter, _wp2_curr, _wp2_next = \\\n",
    "                        None, None, None, None\n",
    "                    \n",
    "                lat_n1_lst = []\n",
    "                lon_n1_lst = []\n",
    "                wp_lat_1_lst = []\n",
    "                wp_lon_1_lst = []\n",
    "                lat_n2_lst = []\n",
    "                lon_n2_lst = []\n",
    "                wp_lat_2_lst = []\n",
    "                wp_lon_2_lst = []\n",
    "\n",
    "                for t in range(1, _tmax):\n",
    "\n",
    "                    if t == 1:\n",
    "                        lat_n_1, lon_n_1 = get_next_crd(lat_1, lon_1, hdg_1, spd_1)\n",
    "                        lat_n_2, lon_n_2 = get_next_crd(lat_2, lon_2, hdg_2, spd_2)\n",
    "\n",
    "                    else:\n",
    "                        lat_n_1, lon_n_1 = get_next_crd(lat_n_1, lon_n_1, hdg_1, spd_1)\n",
    "                        lat_n_2, lon_n_2 = get_next_crd(lat_n_2, lon_n_2, hdg_2, spd_2)\n",
    "\n",
    "                    di = calc_coord_dst((lat_n_1, lon_n_1), (lat_n_2, lon_n_2))\n",
    "                    \n",
    "                    lat_n1_lst.append(lat_n_1)\n",
    "                    lon_n1_lst.append(lon_n_1)\n",
    "                    wp_lat_1_lst.append(_wp1_curr[0])\n",
    "                    wp_lon_1_lst.append(_wp1_curr[1])\n",
    "                    lat_n2_lst.append(lat_n_2)\n",
    "                    lon_n2_lst.append(lon_n_2)\n",
    "                    wp_lat_2_lst.append(_wp2_curr[0])\n",
    "                    wp_lon_2_lst.append(_wp2_curr[1])\n",
    "\n",
    "                    if di < ipz_range:\n",
    "                        break\n",
    "\n",
    "                    if not len(wps_seq_1) < 2:\n",
    "                        _hdiff1 = hdg_diff_next_wp(lat_n_1, lon_n_1,\n",
    "                                                   _wp1_curr, _wp1_next)\n",
    "                        dst_currwp_1 = calc_coord_dst((lat_n_1, lon_n_1), _wp1_curr)\n",
    "\n",
    "                        if abs(_hdiff1) < 4 and dst_currwp_1 < 8000:\n",
    "                            hdg_1 = calc_compass_bearing(_wp1_curr, _wp1_next)\n",
    "                            _wp1_curr = next(wp1_curr_iter, sequentialize(_wps_1)[-2])\n",
    "                            _wp1_next = next(wp1_next_iter, sequentialize(_wps_1)[-1])\n",
    "                            \n",
    "\n",
    "                    if not len(wps_seq_2) < 2:\n",
    "                        _hdiff2 = hdg_diff_next_wp(lat_n_2, lon_n_2,\n",
    "                                                   _wp2_curr, _wp2_next)\n",
    "\n",
    "                        dst_currwp_2 = calc_coord_dst((lat_n_2, lon_n_2), _wp2_curr)\n",
    "\n",
    "                        if abs(_hdiff2) < 4 and dst_currwp_2 < 8000:\n",
    "                            \n",
    "                            hdg_2 = calc_compass_bearing(_wp2_curr, _wp2_next)\n",
    "                            _wp2_curr = next(wp2_curr_iter, sequentialize(_wps_2)[-2])\n",
    "                            _wp2_next = next(wp2_next_iter, sequentialize(_wps_2)[-1])\n",
    "                            \n",
    "                            \n",
    "                plt.figure(figsize=(20,20))    \n",
    "                plt.scatter(lat_n1_lst,lon_n1_lst)\n",
    "                plt.scatter(wp_lat_1_lst,wp_lon_1_lst, c='r')\n",
    "                plt.scatter(wp_lat_1_lst[0],wp_lon_1_lst[0], c='g')\n",
    "                plt.scatter(lat_n2_lst,lon_n2_lst)\n",
    "                plt.scatter(wp_lat_2_lst,wp_lon_2_lst, c='r')\n",
    "                plt.scatter(wp_lat_2_lst[0],wp_lon_2_lst[0], c='g')\n",
    "                plt.show()\n",
    "                break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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